Senior Data Analyst & Monetization Lead (Remote)

You’ve spent the last few years as the analyst sitting alongside a mobile squad, close to the tracking, experiments, and numbers behind their decisions. You’ve also led a small team for a while and don’t want to give that up.

This role doesn’t ask you to. You’ll lead our squad analysts while also being the hands-on analyst for Monetization. Roughly half your week in each role, at least at the start. Stepping up to lead here doesn’t mean handing the interesting work to someone else.

You’ll build solid data products, help our Monetization team optimize conversion and revenue, and ensure that our product and engineering teams own the quality of the data they produce. Building this culture is a big part of what we’re hiring for.

Your Mission

• Lead a small team of analysts embedded in our product squads. They measure the impact of engineering builds and help determine next steps.
• Serve as the analyst for Monetization, handling tracking for new features, experiments behind conversion funnels, and reporting for the squad.
• Set the example for how work gets done—write less production code than analysts in your team, and your problem-solving approach will guide them.
• Set the data quality bar: define testing for raw data, transformed data, reporting layers, and anomaly detection before stakeholders notice issues.
• Move responsibility upstream to data-producing teams—expect pushback from those unused to this mindset.
• Own the path from raw event data to curated, ready-to-use datasets in our self-service BI tool.
• Take on the strategy side of squad analytics: how PMs and engineering managers use data in decision-making.

Your Profile

• Experience as an analyst inside a mobile product squad, including event tracking, funnel and user journey analysis, and experiments.
• Managed analysts without stepping away from hands-on work yourself.
• Experimentation is your strength—plenty of A/B tests, bandits, quasi-experiments, and knowledge of Bayesian vs. frequentist approaches.
• Built a data quality regime, including holding back numbers that don’t reconcile and fixing root causes.
• Daily use of SQL and Python, with dbt for data transformation.
• When presenting analysis to PMs, include actionable next steps. If a number is wrong, correct it and improve the process.

Bonus points for:

• Experience with subscription businesses, including mobile gateway SDKs (App Store, Google Play).
• A strong statistics background.
• Experience with Dagster or Airflow for scheduling.
• Familiarity with data catalogues like DataHub.

Our Core Tech Stack

Here’s what we run in production:

• Warehouse: Snowflake
• Transformation & Orchestration: dbt, Dagster
• Experimentation: GrowthBook
• Self-service Analytics: Omni
• ML Workflows: Prefect
• GenAI: Claude

If you’ve worked with a cloud warehouse, dbt, and an experimentation platform, the patterns transfer. AI is part of our workflow—writing and checking code, summarizing data, and keeping documentation current. We expect you to be critical of its outputs.